Predicting risks of acute kidney injury in patients after acute aortic dissection repair surgery: development and assessment of a nomogram prediction model

  AIM  To develop and internally validate the risks of acute kidney injury (AKI) in patients after acute aortic dissection (ATAAD) repair surgery.

  METHODS  The 23 variables of 194 patients with ATAAD confirmed by CTA and surgery in the First Hospital of Lanzhou University from January 2017 to January 2021 were analyzed retrospectively. The incidence of postoperative AKI was counted and divided into non-AKI group and AKI group. The predictive factors were screened by LASSO regression and Logistic regression. The nomogram prediction model was established by R language. The identification, calibration and clinical usefulness of the prediction model were evaluated by C index, calibration chart, ROC curve and decision curve analysis.

  RESULTS  The morbidity of AKI was 43.30%. Logistic regression analysis showed that heart failure, liver insufficiency, renal insufficiency, abnormal ECG, pericardial effusion and renal artery dissection were independent factors affecting AKI after ATAAD repair surgery (P<0.05). Based on the risk factors of AKI morbidity in ATAAD patients, a model containing the independent predictors was developed using R language and presented in nomogram. The model showed good prediction ability, C index was 0.779, ROC AUC value was 0.778 and the calibration was good. In the interval verification, it reached the high C index of 0.748.

  CONCLUSION  AKI nomogram has good predictive ability and can be used to predict AKI in patients after ATAAD repair surgery.